A stochastic approach for self-healing capability evaluation in active islanded AC/DC hybrid microgrids

Abstract

This paper aims to implement a resilience assessment in AC/DC hybrid microgrids using a stochastic simulation approach. Self-healing measures including load shedding, control of distributed generation and flexible devices, like Energy Storage Systems (ESS) and Electrical Vehicles (EVs), are simulated to enable AC/DC hybrid microgrids to supply critical loads in islanded mode, assuming a disconnection of these microgrids from the main AC grid due to a fault. To perform this analysis, a two-stage process is proposed: first, a Monte-Carlo simulation-based stochastic approach is adopted to generate samples to simulate intermittent loads, power generation from Renewable Energy Sources (RESs), and fault occurs in the upstream grid; second, for each sample indicating islanded mode, a grid-connected daily Optimal Power Flow (OPF) is formulated in Mixed-Integer Linear Programming (MILP) form based on minimizing operation cost to withdraw the State of the Charge (SoC) of stationery and traction batteries and electrical vehicles before microgrids may go to islanded mode. Finally, resilience of islanded microgrids are evaluated through some indices. In addition, different strategies are considered for modeling the behavior of both two types of electrical vehicles V1G and V2G. Simulations results show distributed generation and flexible devices might improve resilience in islanded microgrids, optimal daily planning in grid-connected mode could affect it adversely though, due to the low energy available of flexible devices at the islanding moment.